The invention relates generally to turbine engines and, particularly, to estimating turbine engine deterioration rates with noisy data. Specific embodiments of the present technique provide systems and methods for estimating engine deterioration rates for single engine in a fleet and average deterioration rates for a fleet of engines.
There are many benefits to understanding deterioration characteristics in a turbine engine. For example, for a commercial aircraft engine, the management of long term service agreements depends on the ability to accurately forecast overhauls, which is highly dependent on performance deterioration. Better knowledge of deterioration characteristics also improves engine fault diagnostic capability by tightening alert thresholds. Finally, knowledge about the drivers of deterioration characteristics in current designs is used in developing future engines.
A variety of engine performance variables, such as engine exhaust gas temperature (EGT), can be analyzed to estimate engine deterioration. Unfortunately, estimation of engine deterioration rate (also referred to as DetRate) is complicated by several types of defects in the raw data caused by a variety of factors such as sensor calibration shifts, water-wash events, etc. Such defects may include, for example, statistical outliers, step changes in the performance variable, and large X-range gaps (i.e. time gaps).
The current approach for estimating the deterioration rate of a single engine uses a linear regression technique. However, this method disadvantageously assigns a single slope to the entire dataset and, hence, does not mitigate outliers and large X-range gaps in the data. For a fleet of engines, the current approach involves dividing the time scale into segments and manually selecting from the estimated individual engine deterioration rates those that seem reasonable. The selected deterioration rates of individual engines are then combined within each segment to obtain the fleet average. A disadvantage of this method is that it provides no estimate for the error in the average deterioration rate of the fleet.
Accordingly, there is a need for an improved system and method to estimate engine deterioration rates for single engine as well as average deterioration rates for a fleet of engines.